/**
 * Copyright 2010 Neuroph Project http://neuroph.sourceforge.net
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.neuroph.core.transfer;

import java.io.Serializable;

/**
 * Abstract base class for all neuron tranfer functions.
 * 
 * @author Zoran Sevarac <sevarac@gmail.com>
 * @see org.neuroph.core.Neuron
 */
abstract public class TransferFunction implements Serializable {
	
	/**
	 * The class fingerprint that is set to indicate serialization
	 * compatibility with a previous version of the class.
	 */		
	private static final long serialVersionUID = 1L;
        
        /**
         * Output result
         * Used to cache calculated output in order to be  able to reuse it and avoid multiple calculations (especially in getDerivative method).
         * Every time when method getOutput is called output should be stored here.
         */
        protected transient double output; // cached output value to avoid double calculation for derivative

	/**
	 * Returns the ouput of this function.
	 * 
	 * @param totalInput
	 *            total input 
         * @return returns calculated value of the function
	 */
	abstract public double getOutput(double totalInput);

	/**
	 * Returns the first derivative of this function.
	 * Note: should this method should be abstract?
	 * @param totalInput
	 *            total  input
	 */
	public double getDerivative(double totalInput) {
		return 1d;
	}

}
